Artificial neural network-assisted modeling of electroosmotic heat transfer in radiative ternary hybrid nanofluid with gyrotactic microorganisms
Date
2025
Authors
Ali, M.Y.
Rana, B.M.J.
Islam, T.
Hossain, M.S.
Parvez, M.S.
Afikuzzaman, M.
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Journal of Thermal Analysis and Calorimetry, 2025; 150(26):1-30
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Sutterby fluid rheology and electroosmotic phenomena combine the modern electrokinetic transport technologies with the realistic fluid behavior. This enhances predictions that are more accurate, improved designs, and greater performance of a wide array of applications in areas such as process engineering, biotechnology, and so on. In order to capture bioconvective effects, this work models the radiative electroosmotic flow (EOF) of a ternary hybrid nanofluid (TiO2-Al2O3-Fe3O4 in a 50:50 propylene glycol-water base) as a non-Newtonian Sutterby fluid which incorporates gyrotactic microorganisms. For sophisticated heat transfer applications, the framework provides a realistic model by taking into account viscous dissipation, chemical processes, nonlinear radiation, porous media, and Joule heating. The objective of this research is to evaluate and improve the heat transfer performance of a ternary hybrid Sutterby nanofluid by modeling and examining its radiative electroosmotic flow, which incorporates bioconvection, porous media, nonlinear radiation, and various thermophysical factors.
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Copyright 2025 Akadémiai Kiadó Zrt